class_docstr: Class for the manifold of beta distributions.
  
  This is Beta = :math:`R_+^* \times R_+^*`, the upper-right
  quadrant of the Euclidean plane.
  
  Attributes
  ----------
  dim : int
      Dimension of the manifold of beta distributions, equal to 2.
  embedding_space : Manifold
      Embedding manifold.
class_docstr_tok: ["Class","for","the","manifold","of","beta","distributions",".","This","is","Beta","=",":","math",":","`","R_+^","*","\\times","R_+^","*","`",",","the","upper-right","quadrant","of","the","Euclidean","plane",".","Attributes","--","--","--","--","--","dim",":","int","Dimension","of","the","manifold","of","beta","distributions",",","equal","to","2.","embedding_space",":","Manifold","Embedding","manifold","."]
docstr: Sample from the beta distribution.
  
  Sample from the beta distribution with parameters provided by point.
  This gives samples in the segment [0, 1].
  
  Parameters
  ----------
  point : array-like, shape=[..., 2]
      Point representing a beta distribution.
  n_samples : int
      Number of points to sample with each pair of parameters in point.
      Optional, default: 1.
  
  Returns
  -------
  samples : array-like, shape=[..., n_samples]
      Sample from beta distributions.)
docstr_tok: ["Sample","from","the","beta","distribution",".","Sample","from","the","beta","distribution","with","parameters","provided","by","point",".","This","gives","samples","in","the","segment","[","0",",","1","]",".","Parameters","--","--","--","--","--","point",":","array-like",",","shape=","[","...",",","2","]","Point","representing","a","beta","distribution",".","n_samples",":","int","Number","of","points","to","sample","with","each","pair","of","parameters","in","point",".","Optional",",","default",":","1",".","Returns","--","--","--","-","samples",":","array-like",",","shape=","[","...",",","n_samples","]","Sample","from","beta","distributions",".",")"]
code: def sample(self, point, n_samples=1):
      """Sample from the beta distribution.
  
      Sample from the beta distribution with parameters provided by point.
      This gives samples in the segment [0, 1].
  
      Parameters
      ----------
      point : array-like, shape=[..., 2]
          Point representing a beta distribution.
      n_samples : int
          Number of points to sample with each pair of parameters in point.
          Optional, default: 1.
  
      Returns
      -------
      samples : array-like, shape=[..., n_samples]
          Sample from beta distributions.)
      """
      return self._scp_rv.rvs(point, n_samples)
  
file_path: geomstats/geomstats/information_geometry/beta.py
imports: from scipy.stats import beta
  import geomstats.backend
  from geomstats.information_geometry.base import ScipyUnivariateRandomVariable
  from geomstats.information_geometry.dirichlet import DirichletDistributions, DirichletMetric
label_desc: Use image node_id 3 for calling the BetaDistributions obj's underlying member method code with example usage: obj.sample(point, n_samples) and returns: self